Appendix F — Milestone 1

WNBA Performance Analysis

Author

Cate Stacy and Karyna Steele

Project Description

We are analyzing WNBA data from the 2025 season. We plan on exploring factors that contribute to the success of teams and individuals. We have access to play-by-play, team box score, and player box score data.

Research Questions

1) What influences playing time for a WNBA player?

2) What are the characteristics of winning teams? Do these characteristics align with the outcome of the championships?

Inspiration

We were interested in pursuing a project surrounding sports given that it has many statistics. In recent years, women’s basketball has experienced a rapid rise in popularity. This has coincided with the growth of the WNBA, making it an exciting topic to analyze.

Data

Code

library(wehoop)
library(tidyverse)

wnba_pbp <- wehoop::load_wnba_pbp()
wnba_team_box <- wehoop::load_wnba_team_box()
wnba_player_box <- wehoop::load_wnba_player_box()

Implamentation Plan

Clean the data sets (together)

Identify NA values and filter variables we need to answer our research questions

EDA (individually) a.Make visualizations and identify variables that could be valuable for our analysis

Summarize finding and narrow down research questions

Research (individually)

Conduct research about the data (ex. How it was collected)
Do background research on topic

Create preliminary findings presentation (together)

Collaborate on presentation and present to classmates

Create data story and present to class (together)

Ensure that report is clean (hide warnings, ensure there are no long outputs)
Revise according to feedback

Clean up and organize GitHub repository (together)

Add README file

Create presentation slides and video (together)
Evaluation and reflection (individually)

---
title: "Milestone 1"
subtitle: "WNBA Performance Analysis"
authors: "Cate Stacy and Karyna Steele"
format:
  html:
    toc: true
    toc-depth: 2
    embed-resources: true
---

```{r include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE, 
  warning = FALSE,
  message = FALSE,
  fig.height = 2.75, 
  fig.width = 4.25,
  fig.env='figure',
  fig.pos = 'h',
  fig.align = 'center')
```

# Project Description
We are analyzing WNBA data from the 2025 season. We plan on exploring factors that contribute to the success of teams and individuals. We have access to play-by-play, team box score, and player box score data.

# Research Questions

### 1) What influences playing time for a WNBA player?

### 2) What are the characteristics of winning teams? Do these characteristics align with the outcome of the championships?

# Inspiration
We were interested in pursuing a project surrounding sports given that it has many statistics. In recent years, women’s basketball has experienced a rapid rise in popularity. This has coincided with the growth of the WNBA, making it an exciting topic to analyze.

# Data
```{r}
library(wehoop)
library(tidyverse)

wnba_pbp <- wehoop::load_wnba_pbp()
wnba_team_box <- wehoop::load_wnba_team_box()
wnba_player_box <- wehoop::load_wnba_player_box()
```

# Implamentation Plan
1) Clean the data sets (together)
a. Identify NA values and filter variables we need to answer our research questions
2) EDA (individually)
a.Make visualizations and identify variables that could be valuable for our analysis
b. Summarize finding and narrow down research questions
3) Research (individually)
a. Conduct research about the data (ex. How it was collected)
b. Do background research on topic
4) Create preliminary findings presentation (together)
a. Collaborate on presentation and present to classmates
5) Create data story and present to class (together)
a. Ensure that report is clean (hide warnings, ensure there are no long outputs)
b. Revise according to feedback
6) Clean up and organize GitHub repository (together)
a. Add README file
7) Create presentation slides and video (together)
8) Evaluation and reflection (individually)